Big Data Analytics with Spark

A Practitioner's Guide to Using Spark for Large Scale Data Analysis

Éditeur :

Apress

Paru le : 2015-12-29

Big Data Analytics with Spark is a step-by-step guide for learning Spark, which is an open-source fast and general-purpose cluster computing framework for large-scale data analysis. You will learn how to use Spark for different types of big data analytics projects, including batch, interactive, grap...
Voir tout
Ce livre est accessible aux handicaps Voir les informations d'accessibilité
Ebook téléchargement , DRM LCP 🛈 DRM Adobe 🛈
Compatible lecture en ligne (streaming)
62,11
Ajouter à ma liste d'envies
Téléchargement immédiat
Dès validation de votre commande
Image Louise Reader présentation

Louise Reader

Lisez ce titre sur l'application Louise Reader.

À propos


Éditeur

Collection
n.c

Parution
2015-12-29

Pages
277 pages

EAN papier
9781484209653

Auteur(s) du livre


Mohammed Guller is the principal architect at Glassbeam, where he leads the development of advanced and predictive analytics products. He is a big data and Spark expert. He is frequently invited to speak at big data–related conferences. He is passionate about building new products, big data analytics, and machine learning.Over the last 20 years, Mohammed has successfully led the development of several innovative technology products from concept to release. Prior to joining Glassbeam, he was the founder of TrustRecs.com, which he started after working at IBM for five years. Before IBM, he worked in a number of hi-tech start-ups, leading new product development.Mohammed has a master's of business administration from the University of California, Berkeley, and a master's of computer applications from RCC, Gujarat University, India.

Caractéristiques détaillées - droits

EAN PDF
9781484209646
Prix
62,11 €
Nombre pages copiables
2
Nombre pages imprimables
27
Taille du fichier
4997 Ko
EAN EPUB
9781484209646
Prix
62,11 €
Nombre pages copiables
2
Nombre pages imprimables
27
Taille du fichier
2181 Ko

Suggestions personnalisées